DATA1001 Project 2 NYPD Crime Dataset

Author

550597500

1 Client Bio

Client: New York Police Department

The New York Police Department (NYPD) is responsible for “law enforcement, traffic management, counter-terrorism, and emergency response” in the Bronx, Brooklyn, Manhattan, Queens, and Staten Island (NYPD, n.d.). The NYPD’s mission includes enhancing the quality of life in New York City while promoting transparency and impartiality when enforcing the law.

2 Recommendation

The NYPD should collaborate with the Department of Education to foster different curriculums that suit the needs of students with low literacy rates, especially in the Bronx and Brooklyn. If the student is still not inclined, vocational programs focusing on practical skills and trades should be offered as a substitute.

3 Evidence

Rehabilitating older criminals can be more challenging due to cognitive decline, undesired behavioural characteristics, and social isolation (Logan et al. 2025). Once released, the majority of these criminals are unable to reintegrate into society due to societal and legal factors, which results in the United States having a recidivism rate of 70% within 5 years (Hayden, 2023, p. 470). As such, the NYPD has taken preventative measures targeting offenders under 18 to lessen the burden on the judicial system.

The Raise the Age legislation enacted in 2017 “changed the age that a child can be prosecuted as an adult to 18 years of age in criminal cases”, which reduced the number of criminal complaints for under-18 offenders (NY Courts, 2019). Although the NYPD prioritised intervention and treatment for non-criminal youth offenders, its efforts could be better realised by improving education standards in historically impoverished and high crime rate boroughs of the Bronx and Brooklyn. This effort would decrease the number of incarcerated youth, which will reduce the incarcerated population while alleviating pressures on the judicial system and correctional facilities.

3.1 Relationship between Education and Incarceration

Empirical studies have portrayed that “crime and education are inextricably tied together”, as students who fail in school are stuck in a negative virtuous cycle of not understanding the curriculum and slowly pushed out of the school (Vacca, J. 2008, p. 1055). Thus, failing students may seek out other areas in which they may excel, increasing the likelihood of the student participating in criminal activities (Vacca, J. 2008).

Analysing New York City’s 2014 Scholastic Aptitude Test (SAT) results revealed that the Bronx and Brooklyn scored the lowest average SAT scores at 1203 and 1230 respectively, with the weakest categories being reading and writing. Low literacy rates can result in higher unemployment and incarceration rates and reduced potential income.

Borough Count avg_SAT_math avg_SAT_reading avg_SAT_writing avg_SAT_total
Bronx 118 404 403 396 1203
Brooklyn 121 416 411 403 1230
Manhattan 106 456 445 439 1340
Queens 80 462 443 440 1345
Staten Island 10 486 478 474 1438

A statistical analysis of crime in India and literacy rate yielded a moderately negative correlation, as seen below (Amin, 2019. p. 62). Furthermore, a cross-examination between state IQ and FBI crime statistics suggested that “the prevalence of both violent and property crimes is associated with lower state IQs” (Bartels et al. 2010. p. 579).

However, there are limitations to this report as certain environmental factors, such as a child’s safety are difficult to quantify. Moreover, parental figures and a sense of community in a student’s life can play a pivotal role in their academic success in school and higher education.

4 Ethics Statement

This report demonstrates the shared value of truthfulness in the International Statistical Institute by ensuring the data is obtained from reputable sources and is not skewed to portray a misleading relationship between variables. The author avoided conflicts of interest by having no relationships with the aforementioned parties in the report.

5 AI usage statement

No artificial intelligence tool or large language model was utilised in the completion of this report.

6 Acknowledgements

6.1 General Resources

6.2 References